Searching for Connections between Teacher Program Applicant Information and Selection, and STEM Teacher Retention and Effectiveness to Inform Teacher Recruitment and Education

该项目旨在满足国家对高素质科学、技术、工程和数学(STEM)教师的需求。为此，它将寻找潜在教师候选人的信息之间的联系，如考试成绩和STEM成绩；他们被STEM教师教育计划的录取和入学；以及他们后来作为STEM教师的保留和有效性。人们对提高美国STEM教师队伍的质量有着浓厚的兴趣。然而，令人惊讶的是，关于教师教育项目申请中的信息是否可以预测STEM教师的留任和有效性，人们知之甚少。这项研究旨在产生关于教师教育项目招生的经验证据，这是影响国家STEM教师队伍质量的关键第一步。需要调查的具体研究问题包括：1.特定类型的申请者信息是否预测STEM教师的留任？2.申请者信息是否预测STEM教师的有效性？3.申请者信息是否在有效性分布上对保留率有不同的预测？4.申请者信息是否对高需求教育机构的保留率和有效性有差异的预测？对这些问题的回答可能会揭示申请者信息和教师成绩之间的联系。这些信息可以为STEM教师教育项目的招聘和录取提供决策依据。因此，该项目有可能改善国家确保高素质STEM教师队伍的整体战略。该项目是美国研究院教育研究纵向数据分析中心、华盛顿州教育研究和数据中心与华盛顿州五所培养STEM教师的大学(华盛顿州中部大学、太平洋路德大学、华盛顿大学、华盛顿州大学和华盛顿州西部大学)合作的项目。这项研究是通过有关华盛顿州学生和教师的全州数据进行的，这些数据包括：1)来自该州所有高需求教育机构的数据；2)该州公立学院和大学录取的STEM教师候选人的大学成绩单数据；以及3)五所合作大学的招生程序和招生数据。这些量化数据的来源将被结合起来，以便对大学申请者的属性进行基于回归的分析，这些属性与STEM教师的有效性和保留率相关。该项目还将收集合作大学教师的定性数据，以更好地了解STEM教师教育项目的教师对未来教师候选人的重视，以及他们的价值是否与参与大学的录取和入学有关。该项目以经济和社会文化理论为依据。经济学理论基础将教师教育项目置于公共劳动力市场中，在公共劳动力市场中，申请者信息根据决策者的背景、经验和社会背景进行过滤。鉴于这项工作的潜在相关性，项目成果不仅将通过学术期刊传播，而且还将通过国家和州会议、项目网站以及与全州各地的利益攸关方举行的项目会议来传播。这个Track 4：Noyce研究项目是由Robert Noyce教师奖学金计划(Noyce)支持的。Noyce计划支持有才华的STEM本科专业和专业人员成为有效的K-12 STEM教师，并支持经验丰富、模范的K-12 STEM教师成为高需求学区的STEM硕士教师。它还支持对高需求学区K-12 STEM教师的持久性、保留率和有效性的研究。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This project aims to serve the national need for high-quality science, technology, engineering, and math (STEM) teachers. To do so, it will look for connections between information from potential teacher candidates, such as test scores and STEM grades; their admittance to and enrollment in STEM teacher education programs; and their later retention and effectiveness as STEM teachers. There is intense interest in improving the quality of the U.S. STEM teacher workforce. However, surprisingly little is known about whether information in applications to teacher education programs predict or do not predict STEM teacher retention and effectiveness. This study is designed to generate empirical evidence about admissions into teacher education programs, the crucial first step to influencing the quality of the nation’s STEM teacher workforce. The specific research questions to be investigated include: 1. Are specific types of applicant information predictive of STEM teacher retention? 2. Is applicant information predictive of STEM teacher effectiveness? 3. Is applicant information differentially predictive of retention along the effectiveness distribution? 4. Is applicant information differentially predictive of retention and effectiveness in high-need educational agencies? Answers to these questions may reveal connections between applicant information and teacher outcomes. Such information could inform decisions about recruitment and admissions into STEM teacher education programs. As a result, the project has the potential to improve the nation’s overall strategy for ensuring a high-quality STEM teacher workforce. This project is a collaboration between the Center for Analysis of Longitudinal Data in Education Research at the American Institutes for Research, Washington State’s Education Research and Data Center and five Washington State universities that prepare STEM teachers (Central Washington University, Pacific Lutheran University, University of Washington, Washington State University, and Western Washington University). This research study is made possible by statewide data about students and teachers in Washington that include: 1) data from all high-need educational agencies in the state; 2) college transcript data about STEM teacher candidates enrolled in public colleges and universities in the state; and 3) data about admissions processes and admissions from the five collaborating Universities. These sources of quantitative data will be combined to permit regression-based analyses of the attributes of college applicants that are correlated with STEM teacher effectiveness and retention. The project will also collect qualitative data from faculty at collaborating universities to better understand what faculty in STEM teacher education programs value in prospective teacher candidates and whether what they value is related to admission and enrollment in the participating universities. The project is informed by economical and socio-cultural theories. The economical theoretical basis places teacher education program operations within a public labor market in which applicant information is filtered by decision makers’ backgrounds, experiences, and social contexts. Given the breadth of potential relevance of this work, project results will be disseminated not only through academic journals, but also through national and state conferences, project websites, and a project conference with stakeholders from around the state. This Track 4: Noyce Research project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 STEM teachers to become STEM master teachers in high-need school districts. It also supports research on the persistence, retention, and effectiveness of K-12 STEM teachers in high-need school districts.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.